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The potential mechanism of the Ruhao Dashi formula in treating acute pneumonia via network pharmacology and molecular docking

Acute pneumonia (AP) has a high seasonal prevalence every year, which seriously threatens the lives and health of patients. Six traditional Chinese medicines in Ruhao Dashi formula (RDF) have excellent antiinflammatory, antibacterial, and antiviral effects. RDF is commonly used in the clinical treat...

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Detalles Bibliográficos
Autores principales: Yi, Xiu-Xiu, Zhou, Hui-Fen, He, Yu, Yang, Can, Yu, Li, Wan, Hai-Tong, Chen, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019263/
https://www.ncbi.nlm.nih.gov/pubmed/36930096
http://dx.doi.org/10.1097/MD.0000000000033276
Descripción
Sumario:Acute pneumonia (AP) has a high seasonal prevalence every year, which seriously threatens the lives and health of patients. Six traditional Chinese medicines in Ruhao Dashi formula (RDF) have excellent antiinflammatory, antibacterial, and antiviral effects. RDF is commonly used in the clinical treatment of AP. However, the mechanism and target of RDF are unclear. Therefore, this study aimed to use network pharmacology and molecular docking to evaluate the target and mechanism of RDF in the treatment of AP. METHODS: The Herbs and Disease Gene databases were searched to identify common targets of AP and RDF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-Protein Interaction (PPI) network analyses were performed to identify the potential molecular mechanisms behind RDF. Molecular docking was performed to compare the binding activities of the active molecules with that of the target protein. RESULTS: The “drug-component-common target” network contained 64 active compounds and 134 targets. GO and KEGG analyses indicated that RDF could act by regulating cell death, cell proliferation, apoptosis, and hypoxic response. The PPI network and “pathway-target” network identified 31 core targets. Molecular docking revealed that the 14 active ingredients of RDF bind vigorously to the core targets. CONCLUSION: Through network pharmacology and molecular docking, we found that RDF contains 14 active components and 31 core AP targets. These targets were linked to the development of an antiinflammatory response and could be used to develop new drugs to treat AP.